Récompenses

Eneko Agirre, Gorka Azkune, Jon Ander Campos, Arantxa Otegi, Aitor Soroa

eHealth-2020 (2020)


Eneko Agirre, Gorka Azkune, Jon Ander Campos, Arantxa Otegi, Aitor Soroa

Outstanding Paper award (top 2%) at COLING (International Conference on Computational Linguistics). (2020)

COLING kongresuan Jon Ander Camposen, Arantxa Otegiren, Aitor Soroaren, Eneko Agirreren eta Gorka Azkuneren na “Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning” nabarmendu diren artikuluen artean hautatua izan da.

Eneko Agirre, Jon Ander Campos, Aitor Soroa

Honorable mention paper award (top 1%) at EMNLP (Conference on Empirical Methods in Natural Language Processing) (2020)

The paper, “Spot the Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems,” was among the four articles given an honorable mention for the Best Paper Award, which means it was at the top %1 of all accepted papers.

Eneko Agirre

COVID-19 Open Research Dataset Challenge (CORD-19) (2020)

The competition CORD-19 (COVID-19 Open Research Dataset Challenge) has been organized by several organizations such as Allen Institute for AI, Chan Zuckerberg Initiative, Georgetown University, Microsoft Research, National Institutes of Health and The White House Office of Science and Technology Policy. The organization has made available to the global research community more than 50,000 scientific articles on COVID-19, SARS-CoV-2 and other coronavirus. At the same time, they issue a call to action to artificial intelligence researchers to apply the recent advances in natural language processing, in order to help scientists fighting COVID-19 disease to find necessary information in the scientific literature.


Alberto Blanco, Alicia Pérez, Arantza Casillas

CodiEsp-D. Main evaluation metric: Mean Average Precision. (2020)

The CodiEsp Track is part of the CLEF 2020 conference. CLEF 2020 consists of an independent peer-reviewed conference on a broad range of issues in the fields of multilingual and multimodal information access evaluation, and a set of labs and workshops designed to test different aspects of mono and cross-language Information retrieval systems.

Rodrigo Agerri, German Rigau

Winner of the Capitel@IberLEF 2020 shared task on Named Entity Recognition (NER) for Spanish (2020)

Rodrigo Agerri Ixakideak CAPITEL@IberLEF2020 lehiaketara aurkeztu dituen hiru sistemak lehenengo hiru postuetan sailkatu dira gaztelaniazko artikulu periodistikoetan agertzen diren entitate-izenak biltzeko eta sailkatzeko atalean. (Sub-task 1: Named Entity Reconition and Classification in Spanish News Articles).